43 results about "Life cycle costs" patented technology

The invention discloses an AC pavement full-life cost and carbon emission prediction method based on a fatigue curve, and the method comprises the steps: modeling an asphalt pavement structure of a structure A and a structure B, and enabling the structure A and the structure B to be different in surface layer material and surface layer thickness; the structure A adopts a surface layer material with a known PQI exponential decay rule, and the structure B adopts a novel surface layer material to be calculated; respectively carrying out fatigue tests on surface layer materials of the structure A and the structure B to obtain respective fatigue curves; performing PQI-damage curve fitting on the structure A to obtain fitting parameters; modeling through fatigue index migration, predicting a PQI curve of the structure B, and determining a maintenance scheme of the structure B according to the PQI index of the structure B; and calculating the whole life cycle cost and carbon emission of the structure B. According to the method, the repair time interval during the road use period can be quantitatively predicted, so that the whole life cycle cost and carbon emission of the road structure are calculated, and the adaptability evaluation efficiency of the new material pavement structure in the early stage is improved.

The invention discloses a concrete bridge preventive maintenance decision-making method based on degradation prediction, and relates to the technical field of bridge degradation prediction maintenance, and the method comprises the steps: collecting the degradation characteristic data of a concrete bridge through a bridge detection device; according to the method, various types of degradation characteristic data are collected through the bridge detection equipment, the standardized bridge state characteristic vector set is generated, the data-mechanism fusion inversion model is adopted, the actually collected data and the inherent mechanism of bridge degradation are combined, the estimation result is made to better conform to the actual situation, and the estimation accuracy is improved. Dynamic data assimilation is carried out according to a state space model, a probabilistic estimation set of a degradation driving state is input into a predetermined bridge degradation mechanism model for long-term deterministic simulation prediction to generate a plurality of future performance degradation paths, and all the paths form a degradation track cloud picture reflecting prediction uncertainty; the optimal maintenance strategy set can reduce the expected life cycle cost to the maximum extent on the premise that the bridge maintenance requirement is met.

The invention discloses a multi-dimensional evaluation method of a blast furnace process extreme energy efficiency technology, and relates to the field of steel production energy efficiency evaluation. Aiming at six extreme energy efficiency technologies of a blast furnace process, a'technical unit energy-saving cost (CCEa)-net present value (NPV)-internal return rate (IRR) 'ternary index system is constructed, an energy-saving supply curve and a cost-benefit analysis method are combined, and comprehensive evaluation is realized through four steps: calculating the energy-saving and emission-reducing potential when the blast furnace uses anthracite, and introducing exclusive emission factor correction; calculating the unit energy-saving cost considering the multi-pollutant synergistic benefit, and combining the exclusive reachable rate of the technology; the full-life-cycle cost effectiveness is analyzed from the perspective of enterprises, and technology maturity correction is introduced; and carrying out dynamic weighted sorting based on a TOPSIS method, and outputting technical priorities. The method breaks through the limitation of single-dimensional evaluation, realizes the collaborative evaluation of economic and environmental benefits, and provides a decision basis for the low-carbon transformation of the blast furnace.

The present application proposes a multi-time scale based micro-grid multi-element energy storage collaborative optimization method and system, which takes the lowest life cycle cost as the core optimization target, considers the flexible adjustment ability of hydrogen energy storage system, electrochemical energy storage system and demand response, and constructs a multi-time scale micro-grid multi-element energy storage collaborative optimization configuration model; the first stage and the second stage constraint conditions of the micro-grid multi-element energy storage collaborative optimization configuration model are constructed; the improved column generation algorithm is used to solve the micro-grid multi-element energy storage collaborative optimization configuration model, and the optimal capacity configuration scheme and real-time operation optimization strategy of the micro-grid are obtained. Through multi-time scale modeling and two-stage collaborative optimization solution, the present application quantifies the internal correlation between multi-element energy storage configuration and micro-grid energy balance, significantly reduces the system operation cost, and takes into account the effectiveness and economy of the configuration scheme, thereby providing technical support for stable and efficient operation of the micro-grid.

The invention relates to the technical field of power distribution network planning, and particularly discloses a power distribution network optical storage collaborative planning method considering delay of power grid upgrading, a double-layer optimization model of outer-layer locating and sizing-inner-layer operation scheduling is constructed, and the outer layer takes the minimum life cycle cost and the controllable risk as targets and is brought into the power grid upgrading to delay the present value income; and an inner layer optimizes a typical sunlight storage operation strategy, adopts a second-order cone programming technology to process power flow constraints, and introduces a conditional value-at-risk to quantify a scene fluctuation risk. According to the method, the whole life cycle cost of the system is reduced, the new energy consumption capability and the planning scheme robustness are improved, and an economical and efficient planning path is provided for the power distribution network under high-proportion new energy access.

The invention discloses an offshore wind power sending scheme selection method and device, terminal equipment and a storage medium, and belongs to the technical field of wind power, and the method comprises the steps: obtaining a plurality of to-be-decided offshore wind power sending schemes of a target offshore wind plant, and carrying out the decision making of each to-be-decided offshore wind power sending scheme; according to the initial investment cost parameter, the operation cost parameter and the scrap cost parameter of each facility in the current offshore wind power delivery scheme to be decided, calculating the whole life cycle cost; and calculating the reliability according to the topological structure of the offshore wind power system, the fault rate of the submarine cable system, and the fault rate and the fault repair time of each component of the converter station subsystem, and taking the scheme with the optimal reliability and full life cycle cost in each offshore wind power delivery scheme to be decided as a selected scheme. By implementing the method, the problems of one-sided selection of an offshore wind power sending scheme and no practicability caused by incomplete cost analysis due to the fact that only the initial investment cost is considered during economic evaluation in the prior art can be solved.

The present application proposes a new energy storage system capacity configuration method based on full life cycle cost optimization, relates to the technical field of energy storage capacity configuration optimization, and establishes an annualized net income objective function by respectively constructing an annualized investment cost model, an annualized operation and maintenance cost model and an annualized total income model related to the capacity configuration of the energy storage system. Based on the minimum energy capacity constraint, the actual operation efficiency constraint and the annual throughput energy constraint required to meet the fluctuation suppression of new energy output of the energy storage system, the annualized net income objective function is converted to obtain the converted annualized net income objective function; based on the converted annualized net income objective function, the unit capacity annual net income function is obtained, and the energy storage capacity configuration is carried out based on the unit capacity annual net income objective function to obtain the optimal capacity configuration result. The present application fully considers the implicit influence of the full life cycle of energy storage, improves the scientificity and reliability of energy storage capacity configuration, and further improves the construction quality of new energy.

The application discloses a phase change material-operation parameter integrated intelligent optimization method for low-carbon buildings, which jointly determines phase change material parameters and operation strategies under multiple meteorological scenes, optimizes and stabilizes the thermal performance of a building envelope, simultaneously considers annual energy consumption, peak load, unsatisfied hours, annual carbon emission and life cycle cost (LCC), and outputs an interpretable parameter interval and an engineering operation rule. The application realizes material-operation collaborative decision, cross-climate small sample fast generalization and interpretable recommendation, significantly reduces trial and error cost, and improves the comprehensive performance and reliability of energy efficiency, comfort and carbon emission reduction.

An artificial intelligence-based document and life cycle cost analysis method for solar energy contracts. This method includes two main modules, the AI-based document analysis module and the life cycle costs analysis module. The AI-based document analysis module uses natural language processing (NLP) and a generative pre-trained transformer (GPT) to summarize the key insights and deficiencies of a solar energy proposal or contract and extract the necessary input data for a life cycle cost analysis. The life cycle cost analysis module accepts the input data from the AI-based document analysis module, acquires additional data from other sources like the internet and runs the life cycle cost analysis for the solar energy proposal or contract. The entire process is automated to minimize human error and maintain high industry standards from start to finish. This ensures that the results are both professional and comprehensible for the average property owner.

The application discloses a multi-modal logistics capacity dynamic scheduling method and device for large-scale extraterrestrial facility construction and a storage medium, the method aims at the problems of high single rocket transportation cost and long single space elevator construction period, constructs a whole life cycle cost coupling model integrating a cumulative transportation quantity learning curve and a technology maturity evolution law, adopts a discrete global traversal algorithm to perform multi-dimensional weighted optimization on a construction period and a system total cost in a feasible time domain, determines a global optimal time threshold of capacity mode switching, and introduces a physical disturbance model to correct the robustness of a scheduling scheme. The system automatically generates phased dynamic scheduling instructions based on the optimal time threshold, assigns high-frequency rockets to fill the capacity gap in the early construction period, and switches to a space elevator dominant transportation in the operation period. Through the peak-shaving complementary mechanism of heterogeneous capacity, the application solves the multi-objective conflict of transportation cost and engineering period, and realizes the automatic planning and optimization of the logistics scheme of extraterrestrial infrastructure construction.

The application discloses a highway expansion mode decision method based on a whole life cycle cost benefit, and comprises the following steps: S1, highway expansion period construction cost is estimated; S2, highway expansion period construction carbon emission cost is estimated; S3, highway expansion period operation benefit loss is estimated; S4, highway operation period operation benefit is estimated; S5, highway expansion operation period operation cost is estimated; S6, highway expansion period and operation period vehicle operation carbon emission cost are estimated; S7, based on whole life cycle cost benefit analysis, the expansion scheme is decided.The application considers the construction and operation period carbon emission cost and the expansion period operation benefit loss, so that the whole life cycle cost benefit system of the highway expansion project is more perfect.Facing different expansion modes, the method can be used to complete the total cost benefit analysis of the construction period and the operation period, and the generality of the decision method is improved.

The invention discloses a method and a system for evaluating the life cycle cost of a subway freight system under passenger and freight collaboration. The method comprises the following steps: constructing a life cycle cost model of the subway freight system under passenger and freight collaboration, wherein the life cycle cost model comprises four stages of decision design, construction, operation maintenance and scrap recovery; determining a key cost factor influencing the cost of each stage of the subway freight system under the whole life cycle cost model, and constructing a whole life cycle cost factor relation model of the subway freight system under passenger and freight cooperation based on each cost factor influence factor; and based on the whole-life-cycle cost motivation relationship model and the passenger and freight income of the subway freight system under passenger and freight collaboration, predicting and evaluating the minimization of the whole-life-cycle cost or the maximization of the benefit of the subway freight system under passenger and freight collaboration. By constructing a cost calculation framework and model, key cost causes are identified and quantified, and accurate evaluation and effective management of the M-ULS cost are realized.

The invention provides a design method for reducing the whole life cycle cost of electronic hardware equipment, which relates to the field of electronic equipment management and comprises the following steps: S1, importing a component list of an initial design scheme; s2, determining an alternative replacement component for each component in the list, and forming a component alternative replacement mapping table; s3, constructing an alternative design scheme set based on the mapping table; s4, reliability evaluation is carried out on each alternative design scheme in the scheme set, and the severity level fault rate and the total product fault rate of each scheme are obtained; s5, calculating the whole life cycle cost of each scheme based on a reliability evaluation result; and S6, comparing the whole life cycle cost of all the alternative design schemes, and selecting the scheme with the optimal cost as the final design scheme. According to the method, the product life cycle cost formed by the manufacturing cost, the maintenance cost and the fault influence cost is reduced in the design stage of the electronic equipment, and comprehensive optimization of the economical efficiency and the reliability of the electronic equipment is achieved.

The invention discloses a self-resetting bridge pier structure with high lateral bearing capacity resistance and a design method thereof, and relates to the field of seismic resistance. The structure comprises a bearing platform, a structural assembly of an upper and lower assembly section of a pier body, a prestressed assembly of an unbonded prestressed tendon and an anchorage device, a buckling-restrained brace damper with a connecting piece, and contact assemblies such as a contact steel plate and a shear key, and an assembly seam is moved upwards to the lower part of the pier body. The design method comprises the step of calculating the yield bending moment of the assembly interface, the height of the assembly seam and the reinforcing height. By optimizing the position of an assembly seam, shortening a lateral force arm and combining the synergistic effect of multiple heavy assemblies, on the premise that structural damage is not increased, the lateral bearing capacity of the self-resetting pier meets the design requirement of a ductile pier, the self-resetting performance is stable, the residual displacement angle is smaller than 0.5%, low damage and high energy consumption are achieved, the whole life cycle cost is reduced, and traffic safety is guaranteed.

The invention discloses a peak regulation type energy storage equivalent capacity conversion method and system considering economic cost constraints. The method comprises the following steps: acquiring energy storage and actual operation data of a power grid, and extracting operation parameters of various indexes; determining a reference energy storage system, recording the reference energy storage system as I type, determining various technical parameters of the reference energy storage system, and calculating the whole life cycle total discharge capacity and the whole life cycle cost of the reference energy storage system; solving the to-be-assessed type of stored energy recorded as type II, the required initial configuration capacity and the full life cycle cost thereof by taking the equal total discharge capacity as a target, and recording the to-be-assessed type of stored energy as type II; and S3, judging whether a constraint condition is met or not, and if not, returning to the step S3. According to the method, a double-objective optimization model with technical performance and full-life-cycle economy collaboration is constructed, a multi-type energy storage equivalent peak regulation capacity configuration scheme meeting the technical performance requirement and the economy requirement at the same time is output, and a quantitative and reliable decision basis is provided for energy storage economic operation in a peak regulation scene.

The application discloses a full-life-cycle energy storage-power generation system economic scheduling method, establishes a comprehensive power generation system and energy storage system coupling decision model, that is, a full-life-cycle energy storage-power generation system economic scheduling model, and performs collaborative scheduling through scheduling constraints of thermal power generating units, renewable energy power generating units and the energy storage system in the power generation system and the operation efficiency of the life cycle cost optimization power system, so that the economy and sustainability of the power system are improved.

To create a long-term facility update plan in consideration of a plurality of options such as replacement and repair of power facilities.SOLUTION: According to an aspect of the present disclosure, there is provided a risk transition calculation device including a first risk transition calculation unit configured to calculate a risk transition of each power facility based on failure impact information and failure probability information, a risk reduction width calculation unit configured to calculate a first risk reduction width at the time of replacement of each power facility and a second risk reduction width at the time of one or a plurality of repairs to be performed until replacement of each power facility, and a cost calculation unit configured to calculate a first life cycle cost until each power facility is replaced without being repaired and a second life cycle cost until each power facility is repaired and replaced. A power facility management system includes a determination unit that determines replacement / repair plan information indicating replacement or repair of each power facility on the basis of a lower one of a first life cycle cost and a second life cycle cost, and a plan creation unit that creates a facility replacement plan on the basis of the replacement / repair plan information of each power facility.SELECTED DRAWING: Figure 17

The invention relates to the technical field of anti-floating anchor rods, in particular to an anti-floating anchor rod and a supporting structure thereof, and aims at solving the problems that an existing anti-floating anchor rod and a supporting structure thereof are insufficient in reliability, low in construction efficiency and high in whole life cycle cost. The anti-floating anchor rod and the supporting structure thereof comprise an anti-floating anchor group, a radial expansion anchoring unit and a connecting unit, and the supporting structure is matched for use. The radial expansion anchoring unit is arranged on the anchoring section of the anti-floating anchor set, and anchoring keys are formed through radial expansion by means of the water absorption expansion or thermal expansion characteristic of materials. The supporting structure comprises a base, a vertical positioning unit, a horizontal stabilizing unit and a rapid locking unit and is used for accurately positioning the anchor rod. By the adoption of the technical scheme, the anti-floating bearing capacity can be remarkably improved, the construction reliability is improved, the construction technology is simplified, the construction efficiency is improved, and the whole life cycle cost is reduced.

This application relates to a reverse compensation molding die for the leading edge of wingtip composite materials, belonging to the field of aircraft manufacturing. It features: Source control for improved quality: By integrating deformation control into the molding process, deviations are eliminated at the source, increasing the first-time curing pass rate of parts by over 95%, and achieving a surface profile accuracy better than ±0.05mm. Complete elimination of secondary damage: It avoids any form of "stress assembly" or post-processing correction, ensuring the integrity and durability of the composite material structure. Integration of mold "hardware and software": Curing process knowledge is embedded in the mold in an adjustable form, making the mold a flexible adjustment platform capable of bearing and outputting process variables, achieving knowledge accumulation and reuse. Significant cost reduction and efficiency improvement: It eliminates the cost and time of post-curing shaping tooling and repeated mold repairs, reducing the total life cycle cost of the mold by 70% and significantly shortening the production preparation cycle.

The present application relates to the technical field of bridge technical condition assessment, and particularly relates to a method for calculating the weight of a component of a composite girder bridge based on a stress state, according to the actual stress state of each component of a steel plate composite girder bridge, each stress component of the superstructure is divided, and a weight calculation formula of each component is derived, so that the weight distribution of each component is accurately associated with the stress state, the key stress component is accurately identified and targeted maintenance is implemented, the safety performance of the bridge structure is significantly improved, and the maintenance cost is optimized and the life cycle cost is reduced.

This disclosure pertains to the field of wind power energy storage technology, providing a wind power energy storage optimization method and system based on total life cycle cost. The method includes the following steps: acquiring wind farm operation data; constructing an energy storage control model for wind power fluctuation mitigation based on the acquired data; calculating various costs of the wind farm based on the constructed energy storage control model for wind power fluctuation mitigation to obtain the total life cycle cost of the energy storage system; and optimizing wind power energy storage by minimizing the obtained total life cycle cost as the objective function. This disclosure comprehensively considers fluctuation mitigation effects, energy storage operating status, and configuration costs, providing guidance and practical value for wind power consumption and energy storage integration under the new power system context.

The invention belongs to the technical field of energy storage, and provides an energy storage system capacity optimization configuration method and device, a medium, a product and equipment. The energy storage system capacity optimization configuration method comprises the following steps: constructing a double-target optimization model taking the life cycle cost and the annual average light abandoning rate of an energy storage system as targets; under a set constraint condition, solving the dual-objective optimization model by using a golden leopard optimization algorithm to obtain the optimal capacity configuration of the energy storage system with the minimum life cycle cost and the minimum annual average light abandoning rate of the energy storage system; introducing crossover operation into the golden leopard optimization algorithm, and in the crossover operation, performing crossover operation on individuals of different populations on the same dimension so as to generate new individuals; and meanwhile, the global search and the local search are balanced according to the absolute value of the escape energy. According to the method, high-proportion new energy can be consumed as a target, and the capacity of the new energy is optimally proportioned.

The present application relates to the technical field of energy storage system, and particularly relates to a power scheduling method of an energy storage system and the energy storage system, comprising the following steps: deploying an edge computing node and building a cloud global optimization engine to provide data support for subsequent accurate regulation and control, and guaranteeing the timeliness and integrity of data acquisition; analyzing the energy storage equipment capacity and power grid demand by means of an intelligent algorithm, setting a reasonable response priority and dynamically allocating tasks to ensure efficient use of resources and accurate execution of tasks; adopting an MPC algorithm to take the power grid frequency deviation as an optimization target, rolling optimization of output instruction and correction of prediction error to realize the regulation of the energy storage system on the power grid frequency fluctuation and enhance the stability of the power grid; and taking the minimization of the whole life cycle cost as a target to optimize the long-time energy storage charging and discharging plan, effectively improving the stability of the power grid and the economy of the energy storage equipment operation.

The invention discloses a power grid system regulation and control method and device based on energy storage and a storage medium. The method comprises the steps that an energy storage life degradation model based on the discharge depth, the charge state and the health degree is established, an equal life degradation optimization strategy is put forward, and energy storage and a new energy unit are coordinated and mutually assisted. And constructing a transaction mechanism of the stored energy participating in the electric energy and the frequency modulation market, and determining a marginal clearing price by adopting a Lagrangian method by taking the minimum total operation cost as a target by the scheduling center. The energy storage life degradation model based on the discharge depth, the charge state and the health degree is established, and the equal life degradation optimization strategy is provided, so that the state of the energy storage equipment can be accurately grasped, coordination and mutual assistance of energy storage and a new energy unit are realized, the service life of the energy storage equipment is effectively prolonged, the full life cycle cost of the energy storage system is reduced, and the energy storage efficiency is improved. And economical efficiency and stability of power grid operation are improved.

The embodiment of the invention provides an energy system planning method and device, equipment and a storage medium, and the method comprises the steps: building a double-layer nested optimization model based on a pre-built equipment model of a target energy system, taking the minimization of the total cost of a full life cycle as a target, and correcting the double-layer nested optimization model through a mathematical correction method, and obtaining a single-layer continuous derivable model, solving the single-layer continuous derivable model based on a gradient optimization algorithm, and outputting the optimal capacity configuration and operation strategy of the equipment. According to the method, through discrete variable continuity and double-layer structure flattening, optimization efficiency magnitude improvement is achieved, meanwhile, it is guaranteed that the whole life cycle cost is reduced, and planning efficiency is improved.

The invention provides a reverse design method for a durable railroad bridge pier column in a subtropical ocean environment and a storage medium, and relates to the technical field of structural engineering. The reverse design method can improve design reliability, shorten a design period and reduce full life cycle cost. Comprising the following steps: establishing a material-component-performance three-layer node feature map database of the bridge pier column; reversely deducing initial material parameters meeting performance requirements through a neural network inversion algorithm, and feeding back the deduced initial material parameters to the constructed three-layer node feature map database; outputting a group of regional parameter sets subjected to spatial correlation optimization; generating a fused multi-scale feature vector; and constructing a generative adversarial network for reverse design by taking the generated multi-scale feature vector and the performance demand vector as joint input.

The invention discloses a diesel-electric hybrid power locomotive energy management method based on digital twinning, and the method comprises the steps: constructing and updating a random environment digital twinning model which is used for generating the probability distribution of various random interference factors on a future operation path of a diesel-electric hybrid power locomotive, and in each control period, generating a random environment digital twinning model; generating a scene tree consisting of a plurality of discrete future operation scenes and occurrence probabilities corresponding to the scenes according to the probability distribution, and determining a robust optimal control action of the current control period and enabling the diesel-electric hybrid power locomotive to execute the action by solving a random optimization problem taking the minimum expected comprehensive cost as a target. When the next control period starts, the latest actual operation state of the diesel-electric hybrid power locomotive is obtained to serve as an initial condition, and the steps are repeated; according to the method, the digital twinborn model is constructed, and the fuel cost, the battery life loss cost and the time deviation cost are cooperatively optimized in stochastic optimization, so that robust energy management with optimal full life cycle cost is realized.

The application discloses a kind of mountainous area highway electromechanical equipment's whole life cycle management method, it is related to intelligent transportation infrastructure management technical field, including, standardization equipment operation data set is input into bayesian network evaluation architecture, through multilevel fault propagation path analysis each node posterior probability under environmental parameter dynamic constraint, generates equipment health assessment report;Device control execution state record is fused with historical electromechanical equipment operation data, and equipment whole life cycle degradation curve is constructed by spatiotemporal correlation analysis, and trend feature extraction and signal separation processing are carried out, and equipment whole life cycle analysis report is generated.The application improves the pertinence and timeliness of maintenance decision, realizes the fine monitoring and prediction of equipment whole cycle operation performance, so as to provide reliable basis for scientifically formulating maintenance plan, reducing whole life cycle cost and prolonging equipment service life.

The invention discloses a material structure integrated long-life asphalt pavement design method based on performance interval inversion, and belongs to the technical field of road engineering. The method comprises the following steps: (1) project input and structure primary selection; (2) analyzing structure response and calculating three types of failure indexes; (3) constructing three types of failure utilization rate models; (4) constructing a unified performance boundary function; (5) carrying out material performance interval inversion; (6) screening a material performance database; (7) establishing a whole life cycle cost model; and (8) material-structure joint optimization design. According to the method, structural stress and target life are taken as preconditions, a material performance interval required by each structural layer is reversely solved, multi-constraint optimization is carried out on the basis, and system coupling design of the material and the structure is realized.

The invention provides an intelligent prediction method and system for the whole life cycle cost of power grid equipment, and belongs to the technical field of power grid asset management and artificial intelligence. The method comprises the following steps: constructing a multi-dimensional original data set; performing preprocessing and mechanism characteristic generation on the original data, and constructing a space-time atlas sequence; constructing an STA-STGCN dynamic deep learning model, and performing training and hyper-parameter optimization on the model by using a historical space-time atlas sequence; and inputting a space-time atlas sequence of to-be-predicted equipment into the trained STA-STGCN dynamic deep learning model, outputting a classification cost prediction value and a total prediction value of a specified period in the future, and generating a confidence interval and a risk level of a prediction result through a Monte Carlo Dropout technology. According to the method, prediction with higher precision, higher robustness and better decision value is realized, and lean management requirements of power grid assets are met.